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The Reflector, September 2021
Python Applications for Digital Design and Signal Processing Dates & Times: Thursday, November 11, 2021, videos released weekly 2x1.5 hours Live Workshops: 7:00 - 8:00PM ET; Tuesdays, November 16, 23, 30, December 7 Speaker:
Dan Boschen
Location:
Zoom
This is a hands-on course combining pre-recorded lectures with live Q&A and workshop sessions in the popular and powerful open-source Python programming language.
while bringing forward the signal processing tools for frequency and time domain analysis.
Jupyter Notebooks: This course makes extensive use of Jupyter Notebooks which combines running Python New Format with Pre-Recorded Videos: The course code with interactive plots and graphics for a rich user format has been updated to release pre-recorded video experience. Jupyter Notebooks is an open-source weblectures that students can watch on their own sched- based application (that can be run locally) that allows ule, and an unlimited number of times, prior to live Q&A users to create and share visually appealing docuworkshop sessions on Zoom with the instructor. The ments containing code, graphics, visualizations and invideos will also be available to the students for viewing teractive plots. Students will be able to interact with the for up to two months after the conclusion of the course. notebook contents and use “take-it-with-you” results for future applications in signal processing. Overview: Dan provides simple, straight-forward navigation through the multiple configurations and options, Target Audience: This course is targeted toward users providing a best-practices approach for quickly getting with little to no prior experience in Python, however faup to speed using Python for modelling and analysis miliarity with other modern programming languages and for applications in signal processing and digital design an exposure to object-oriented constructs is very helpverification. Students will be using the Anaconda distri- ful. Students should be comfortable with basic signal bution, which combines Python with the most popular processing concepts in the frequency and time domain. data science applications, and Jupyter Notebooks for a Familiarity with Matlab or Octave is not required, but rich, interactive experience. the equivalent operations in Python using the NumPy package will be provided for those students that do curThe course begins with basic Python data structures rently use Matlab and/or Octave for signal processing and constructs, including key “Pythonic” concepts, fol- applications. lowed by an overview and use of popular packages for Benefits of Attending / Goals of Course: Attendees will scientific computing enabling rapid prototyping for sys- gain an overall appreciation of using Python and quickly tem design. get up to speed in best practice use of Python and related tools specific to modeling and simulation for signal During the course students will create example designs processing analysis and design. including a sigma delta converter and direct digital synthesizer both in floating point and fixed point. This will All set-up information for the installation of all tools include considerations for cycle and bit accurate mod- will be provided before the start of class. els useful for digital design verification (FPGA/ASIC),
